Internet of Entities (IoE): A Blockchain-based Distributed Paradigm for

Data Exchange between Wireless-based Devices

Roberto Saia, Salvatore Carta, Diego Reforgiato Recupero and Gianni Fenu

Department of Mathematics and Computer Science,

University of Cagliari, Via Ospedale 72 - 09124 Cagliari, Italy

Keywords:

Internet of Things, Internet of Entities, Mobile Network, Blockchain, Distributed Ledger.

Abstract:

The exponential growth of wireless-based solutions, such as those related to the mobile smart devices (e.g.,

smart-phones and tablets) and Internet of Things (IoT) devices, has lead to countless advantages in every area

of our society. Such a scenario has transformed the world a few decades back, dominated by latency, into a new

world based on an efﬁcient real-time interaction paradigm. Recently, cryptocurrency has contributed to this

technological revolution, whose fulcrum is a decentralization model and a certiﬁcation function offered by the

so-called blockchain infrastructure, which makes it possible to certify the ﬁnancial transactions, anonymously.

This paper aims to indicate a possible approach able to exploit this challenging scenario synergistically by

introducing a novel blockchain-based distributed paradigm for data exchange between wireless-based devices

deﬁned Internet of Entities (IoE). It is based on two core elements with interchangeable roles, entities and

trackers, which can be implemented by using existing infrastructures and devices, such as those related to

smart-phones, tablets, and IoT systems. The employment of the blockchain-based distributed paradigm allows

our approach ensuring the anonymization and immutability of the involved data, which is key in many scenar-

ios and domains (e.g. ﬁnancial applications, health and legal applications dealing with personal and sensitive

data), requirements more and more searched in recent innovations. The possibility to exchange data among a

huge number of devices gives rise to a novel and widely exploitable data environment, whose applications are

possible in different domains, such as, in Security, eHealth, and Smart Cities.

1 INTRODUCTION

Currently, the everyday life is dominated by an enor-

mous number of wireless-based smart devices that al-

low us to perform in real-time an increasing number

of activities that until a few years ago were time con-

suming, such as requests for documents, job applica-

tions, purchases, authentication (Abate et al., 2017;

Barra et al., 2018) and so on. Such opportunities

have been further revolutionized by the decentral-

ized paradigms introduced with the advent of the Bit-

coin (Bonneau et al., 2015) cryptocurrency, which has

traced a new way to exchange currency. A synergis-

tic combination of security and anonymity stands at

the base of its success, since this paradigm allows

the users to exchange currency without the need to

involve trusted authorities as intermediary. The strat-

egy behind this revolutionary way to operate is mainly

based on a digital signature scheme, which is com-

bined with the effort needed to solve a quite hard

mathematical problem. The fulcrum of this mech-

anism is an immutable public ledger where all the

transactions are recorded. It is implemented on the

so-called blockchain-based infrastructure by exploit-

ing a distributed consensus protocol that operates in a

peer-to-peer network (Nakamoto, 2008).

The idea on which the proposed IoE paradigm

revolves is the exploitation of the wireless-based

ecosystem, where some existing devices (hereinafter

referred to as trackers) are used in order to track the

activity of other devices associated to people or things

(hereinafter referred to as entities), registering a series

of immutable information about the latter by using

the features offered by a blockchain-based distributed

ledger. This idea relies on what afﬁrmed by several

authoritative studies, which indicate that by the end

of this decade the number of smart-phones and tablets

will be about 7.3 billions of units (Pop-Vadean et al.,

2017), as well as the number of IoT devices, which

will be between 20 and 50 billions by 2020 (Reyna

et al., 2018). Although in a rather coarse manner,

Figure 1 shows the placement of the proposed IoE

paradigm, with respect to already existing wireless-

based scenarios.

Saia, R., Carta, S., Recupero, D. and Fenu, G.

Internet of Entities (IoE): A Blockchain-based Distributed Paradigm for Data Exchange between Wireless-based Devices.

DOI: 10.5220/0007379600770084

In Proceedings of the 8th International Conference on Sensor Networks (SENSORNETS 2019), pages 77-84

ISBN: 978-989-758-355-1

Figure 1: IoE Placement.

The implementation of such a paradigm can be

made by adding simply functionalities to the exist-

ing devices used as trackers (IoT, smart-phones, etc),

since we only need to append few entity data (i.e.,

unique identiﬁer and sensors data) with few tracker

data (e.g., time-stamp, geographic location, sensors

data, etc.) and sent them to a blockchain-based dis-

tribute ledger. It should be observed that in case of

mobile devices (e.g., smart-phones and tablets) such

an operation can be easily performed by installing an

application, whereas for other devices (e.g., IoT) it

can be done through a software update.

About the entity-side of this scenario, an interest-

ing aspect related to the IoE paradigm is its capability

to use both custom devices (e.g., light wearable de-

vices) and existing widespread devices (e.g., smart-

phones) as entities. In addition, the IoE paradigm

operates anonymously, since only the entity owner

can associate its unique identiﬁer to the registration

performed on the remote ledger through the trackers.

The inclusion, when it is applicable, of one or more

neighbor entities (i.e., those detected by the tracker

near the entity within a given time-frame) offers an

additional tracing opportunity, since it allows us to re-

construct an entity activity in a wide manner, without

jeopardizing the anonymity of the involved neighbor

entities.

It should be observed that there are many areas

where the IoE paradigm can be proﬁtably exploited

(e.g., Security, eHealth, Smart Cities, etc.).

In the security domains, such a paradigm can

represent an effective mechanism for the localiza-

tion of people and things, which exploits both the

huge number of existing wireless-based devices and

the blockchain-based distributed ledger technology,

overcoming the limits of traditional localization ap-

proaches, but without jeopardizing the user privacy.

About the eHealth scenario, all the sensors data

available in the tracker environment (temperature,

humidity, smog, light level, location, altitude, etc.)

can be combined to those provided by a series of

wearable sensors placed on the entity (e.g., heart rate,

pressure, etc.). This conﬁguration allows us to trace,

in an exhaustive manner, the health status of an entity,

highlighting hidden person-environment interactions,

otherwise not obvious. In other words, the data-ﬂow

existing between trackers and entities enriches the in-

formation provided by the individual sensors placed

on an entity body, since the IoE environment allows

us to extend them with the information related to all

the sensors placed on the near involved trackers. This

data-shared modality provides targeted (and more ac-

curate) measurements and/or alerts, since it allows the

system to have an overview of the real health-status of

an entity, with regards to a speciﬁc location and with

regard to some near entities.

Similar interactions between entities and trackers

can be also exploited in the Smart Cities context, rais-

ing a number of interesting applications. Considering

that the trackers can be devices that operate, speciﬁ-

cally, in such a context, their sensors data can be inte-

grated to those related to a group of entities in order

to create functionalities aimed to speciﬁc groups of

users.

The blockchain-based distributed paradigm al-

lows us to ensure the anonymization and immutability

of the involved data, which is crucial in many scenar-

ios and domains, such as those related to the ﬁnan-

cial, health, and legal applications, which deal with

personal and sensitive data. In all the scenarios where

there is no need to obtain information with these char-

acteristics, it is possible to use a canonical distributed-

database solution rather than a blockchain-based one.

Summarizing, this is an approach that leads to-

wards two interesting advantages: it is able to uncover

implicit characteristics of the involved entities by fol-

lowing non canonical criteria; each group of entities

can be anonymously characterized on the basis of the

sensors data of the entities that belong to it.

The main scientiﬁc contributions of this paper are

therefore the following:

i. introduction of the novel concept of entities and

trackers, able to exchange roles, which operates

within a speciﬁc wireless-based environment;

ii. deﬁnition of interaction models between entities

and trackers, and trackers and blockchain-based

distributed ledgers, in terms of unique identiﬁca-

tion of the involved devices and communication

techniques/protocols;

iii. formalization of the entity-to-tracker and tracker-

to-blockchain-based distributed ledger communi-

cation protocol data structures.

The paper is organized into the following sections:

Section 2 provides an overview about the background

and related work; Section 3 reports the adopted for-

mal notation; Section 4 describes the implementation

of the proposed IoE paradigm; Section 5 discusses

about some future directions related to IoE; Section 6

SENSORNETS 2019 - 8th International Conference on Sensor Networks

Figure 2: Mobile Network Structure.

closes the paper with some concluding remarks.

2 BACKGROUND AND RELATED

WORK

This section introduces the most important concepts

related to the context taken into account in this paper.

Mobile Network: A mobile (or cellular) network is

a wireless-based network geographically distributed

in a number of areas deﬁned cells (Rappaport et al.,

1996), as shown in Figure 2. This mechanism based

on cells divides the mobile network area into many

overlapping geographic areas. It can be imagined as a

mesh of hexagonal cells, where each cell has a base-

station at its center. A slight overlapping between

neighbor cells offers to the mobile devices a continue

radio coverage, since in this way they are covered

by at least one base-station. Such a base-station that

serves a cell works as a hub, since the radio signal

transmitted by a mobile device is retransmitted from

the base-station to another mobile device, transmit-

ting and receiving by adopting different frequencies

in order to avoid interferences. In addition, the base-

stations are connected through a central switching ser-

vice that allows them to track the mobile device calls,

transferring these from a base-station to another one,

when a mobile device moves between cells.

The most important characteristics of the current

mobile network that can be proﬁtable exploited in the

proposed IoE paradigm are the wide coverage (that

offer us a stimulating initial environment) and the

high bandwidth (that allows us to quickly transfer the

data between entities and trackers and between track-

ers and distributed ledgers).

Internet of Things: In recent years we have seen

how Internet has given life to a new revolution that

involves billions of devices. These are characterized

by both a low-cost and a capability to communicate in

wireless through Internet. They are the main actors of

this revolution named Internet of Things (IoT). Within

the IoT environment there are heterogeneous devices,

such as computers, smart-phones, wearable devices,

IP cameras, RFID devices, as well as a large number

of actuators and sensors based on low-cost hardware,

which represent the backbone of the IoT environment.

This gives life to a kind of ecosystem founded on

the communication paradigm, considering that each

device is uniquely identiﬁed and all the devices can

communicate with each other without any geographic

limitation by exploiting the Internet. Another impor-

tant IoT characteristic is that each connected device is

uniquely identiﬁed.

Let us start by saying that an IoT device is poten-

tially able to communicate directly with another one,

a common IoT communication paradigm is that ex-

empliﬁed in Figure 5: each device communicates to

the others through two basic activities, publishing and

subscription; they use a protocol in order to publish

data on a server conventionally deﬁned Broker (in the

example of Figure 5, they use one of the most com-

mon IoT protocols, MQTT

); other devices can sub-

scribe the published data by selecting the topic where

it has been stored; the topic represents the channel

that allows a selective intercommunication between

IoT devices.

Blockchain-based Applications: A blockchain, in

the context of the cryptocurrency applications such

as Bitcoin (Nakamoto, 2008) and Ethereum (Wood,

2014), represents a shared and transparent distributed

ledger. It allows the users to perform secure ﬁnancial

transaction by exploiting a cryptographic mechanism

and it can be imagined as an ever-growing chain of

blocks, where each block stores a sequence of trans-

actions that are freely inspectable by anyone and are

tamper-proof at the same time. Each of these blocks

contains the cryptographic signature of the previous

one and this mechanism does not allow anyone to al-

ter or remove a block without the removal of all re-

lated following blocks.

The blockchain functionality can be exploited also

in non-ﬁnancial contexts, in all the cases where an

application needs to ensure trust services. In other

words, such a technology can be used as a platform

to deﬁne the underlying trust level of an application.

The blockchain ability to verify an identity through

a reliable authentication process (Pilkington, 2016)

is indeed exploited in the context of heterogeneous

environments, such us, for instance, those related

to the eHealth (Castaldo and Cinque, 2018), smart

cities (Sun et al., 2016), and IoT (Xu et al., 2018)

applications.

The core of each application based on the

Message Queue Telemetry Transport

Internet of Entities (IoE): A Blockchain-based Distributed Paradigm for Data Exchange between Wireless-based Devices

Figure 3: Blockchain Distributed Public Ledger.

blockchain infrastructure is the Distributed Ledger

Technology (DLT), since it is clear how the identiﬁca-

tion process relies on the functionality offered by such

a ledger, which protects the anonymity of the entities,

assuring at the same time a certain identiﬁcation.

The process of insertion and validation of an

operation (e.g., a ﬁnancial transaction), carried out

by using a distributed public ledger based on the

blockchain, has been exempliﬁed in Figure 3.

Also worth to mention is the work of authors in (Con-

soli et al., 2014c; Consoli et al., 2014a; Consoli et al.,

2014b; Consoli et al., 2017) that presented a prototype

based on the case of Catania, one of the main cities of

Sicily, with the aim of standardizing the Internet of

Things. In particular their aim was to achieve syntac-

tic and semantic interoperability as a result of trans-

forming heterogeneous sources into Linked Data. The

presented data model for smart cities integrates sev-

eral different data sources, including geo-referenced

data, public transportation, urban fault reporting, etc.

The prototype has been embedded into an open, in-

teroperable, cloud-computing-based citizen engage-

ment platform for the management of administrative

processes of public administrations (Recupero et al.,

2016).

3 FORMAL NOTATION

Let us start by saying that we use the term entity to in-

dicate a device designed to operate in a IoE environ-

ment, associated to a person or thing, and that we use

the term tracker to indicate a generic (new or already

existing) device that operates in a wireless-based en-

vironment, which is aimed to interact with the enti-

ties, we introduce the following formal notation:

i. we denote as E = {e

, e

, . . . , e

} a set of entities,

and we use E(e) to indicate such information re-

lated to an entity e;

ii. we denote as E

= {e

, e

, . . . , e

} the entities in

E detected by a tracker within τ seconds after the

detection of an entity (then E

⊆ E), and we use

(e) to indicate such information related to an

entity e;

iii. we denote as L = {l

, l

, . . . , l

} a set of geo-

graphic locations, with l = {latitude, longitude},

and we use l(e) to indicate such information re-

lated to an entity e, when it is detected by a

tracker;

iv. we denote as T = {t

, t

, . . . , t

} a set of time-

stamps, with t = {yyyy-mm-dd-hh-mm-ss}, and

we use t(e) to indicate the time-stamp related to

the detection of an entity e by a tracker;

v. we denote as I = {i

, i

, . . . , i

} a set of (GUIDs)

using the notation i(e) to indicate the GUID as-

sociated to an entity e, as well as the notation

i(tracker) to indicate the GUID associated to a

tracker;

vi. we denote as P = {p

, p

, . . . , p

} a payload,

with p = {key, value}, and we use P(e) to indi-

cate a payload related to an entity e;

vii. we denote as R = {r

, r

, . . . , r

} a set of registra-

tion made on a blockchain-based distribute ledger,

with r = {i(e), E

(e), l(e), t(e), P(e)}, and we use

r(e) and R(e) to indicate, respectively, a registra-

tion related to an entity e and all the registrations

related to that entity.

4 APPROACH FORMULATION

This section describes the implementation of the pro-

posed IoE paradigm, which has been divided into the

following steps:

i. Elements Deﬁnition: it introduces the concept of

entity and tracker in the IoE environment, as well

as the method to use in order to assign a GUID

to them, outlining some possible operative scenar-

ios;

ii. Elements Detection: the detection process of an

entity is here described, from the detection-time

by a tracker to the recording-time of the collected

data on a blockchain-based distributed ledger;

iii. Elements Communication: it formalizes the

data structures and the software procedures able to

merge the information related to the involved en-

tities and trackers, generating the data-structure

Globally Unique IDentiﬁers, whose structure is for-

mally deﬁned in the RFC-4122.

SENSORNETS 2019 - 8th International Conference on Sensor Networks

that represents the information to store on the

blockchain-based distributed ledger.

4.1 Elements Deﬁnition

The concept of entity is usually related to a person,

but it could be also extended to a large number of ob-

jects such as, for instance, vehicles or goods, and each

entity e is always associated to a GUID.

The concept of tracker is instead related to a

generic device able to detect the entities, capturing

their GUIDs and sensors data, and performing a reg-

istration into a blockchain-based distributed ledger.

Such a registration (i.e., the set r) is deﬁned by join-

ing entity and tracker data.

The unique identiﬁer of the trackers could be al-

ready available (e.g., IP-address), while that of the

new entities placed in the IoE environment needs to

be deﬁned and assigned. Its generation can be made

in several ways (Jones et al., 2012; Watson, 1981). In

our IoE paradigm we perform this operation by using

one of the most effective methods, the GUID previ-

ously introduced in Section 3.

Globally Unique Identiﬁer: The Globally Unique

Identiﬁer (GUID), also known as Universally Unique

Identiﬁer (UUID), is a 128-bit integer number which

is commonly used in order to identify resources

uniquely (Leach et al., 2005). If it is necessary, such

an information can be combined with additional infor-

mation (e.g., related to one or more resource charac-

teristics) in order to identify the same device in differ-

ent contexts. Several algorithms able to generate this

information are described in literature (Leach et al.,

2005).

Through the application of the birthday para-

dox (Hankerson et al., 2004; Mironov et al., 2005)

we can obtain a mathematically demonstration of the

Figure 4: IoE Working Model.

Figure 5: IoT Communication Paradigm.

GUID robustness in terms of hash collision probabil-

ity. Considering that a GUID is a 128-bit long num-

ber, we can identify a million billion entities before

we have a one in a billion possibility (i.e., 10

) to get

a collision, as shown in Equation 1, which is based on

the aforementioned birthday paradox.

n ≈

−2

129

· ln(1 − 10

−9

) ≈ 1, 000, 000, 000, 000, 000 (1)

Some considerations can be made about the poli-

cies to adopt in order to assign the GUID to each en-

tity that operates into the IoE environment, assuring

that this information remains stable along the time.

Some solutions involve either a centralized GUID

distribution, such as in (Manku et al., 2003), offered

as service to the users by following a free or paid

modality, or an autonomous generation of this infor-

mation made directly by the users (Leach et al., 2005).

It should be added that in order to distinguish the IoE

devices from the other classes of devices that operate

in the wireless-based environment, it is appropriate to

reserve part of the GUID information for this purpose.

Operative Scenarios: About the hardware to use in

the IoE environment in order to allow the entities to

interact with the trackers, we can outline several sce-

narios:

i. the entity is characterized by limited or absent

hardware resources (e.g., CPU, memory, etc),

then it performs the identiﬁcation process by ex-

ploiting passive technologies such as, for instance,

RFID (i.e., Radio-Frequency IDentiﬁcation). In

this ﬁrst scenario, the tracker must be able to man-

age this identiﬁcation process;

ii. the entity has hardware resources that allow it

to adopt active technologies for the identiﬁcation

process (e.g., 6LoWPAN and ZigBee, both deﬁned

by the technical standard IEEE 802.15.4). This is

the most common scenario, where the entity uses

canonical wireless technologies and the tracker

does not need any additional capability in order

to interact with it;

iii. the entity is able to perform processes that require

considerable hardware/software resources. Such

a scenario allows us to move on the entity-side

some processes usually performed in the tracker-

side and it also allows the entity to handle complex

Internet of Entities (IoE): A Blockchain-based Distributed Paradigm for Data Exchange between Wireless-based Devices

1 2

5 6

11 12

15 16

21 22

25 26

30 31

Entity: GUID

Entity: Local Payload











Entity

Data

Figure 6: Entity-side Data Structure.

processes related to its sensors.

The scenario taken into consideration in this paper

is the second one, where the entity is characterized

by hardware/software resources that allow it to use

active technologies for its identiﬁcation. It allows us

to implement the IoE paradigm immediately and in a

quite transparent way.

4.2 Elements Detection

As shown in the high-level working model of Fig-

ure 4, when an entity e enters within the coverage area

of a tracker, such a tracker detects its identiﬁer i (i.e.,

its GUID), and it creates and submits a registration

r on a blockchain-based distributed ledger. The de-

tection time of an entity e is indicated in Figure 4 as

data capture and it coincides with the time-stamp t,

which represents the point in the space where the en-

tity is detected by a tracker and the r information are

submitted to the blockchain-based distributed ledger.

4.3 Elements Communication

The communication between an entity e and a tracker

can be performed by adopting very simple data struc-

tures, whose possible formalization are proposed in

Figure 6 and Figure 7. They refer, respectively, to the

data structure used to transmit data from an entity to

a tracker (i.e., entity-side) and to the data structure

used to transmit the registration data from a tracker to

the blockchain-based distributed ledger (i.e., tracker-

side).

About the Entity-side data structure, the GUID in-

formation, which is 128-bit long, is stored by using

5 groups of hexadecimal digits, with the following

size: 8 hexadecimal digits, 4 hexadecimal digits, 4

hexadecimal digits, 4 hexadecimal digits, and 12 hex-

adecimal digits. The registration data r are deﬁned by

merging a series of identiﬁcation data (Tracker Pri-

mary Data) with the sensors data related both to the

entities and trackers activity (Tracker Payload Data)

In some contexts, the Payload Data could be partially

(only the entity or tracker sensors data) or completely

absent (no sensors data) and, in this cases, the entity

information will be the GUID, the location, and the

time-stamp.

The hardware/software process performed in the

entity-side is aimed to broadcast its data (GUID and

1 2

5 6

11 12

15 16

21 22

25 26

30 31

Entity: GUID

Entity: Neighbor Entities List

Tracker: Latitude

Tracker: Longitude

Tracker: Timestamp











Tracker

Primary

Data

Entity + Tracker: Global Payload











Tracker

Payload

Data

Figure 7: Tracker-side Data Structure.

local payload) regularly through the wireless func-

tionality. About the tracker-side hardware/software

process, when there are not active other priority tasks,

the tracker operates a listening activity aimed to de-

tect entities in its wireless coverage area, sending the

collected entity and tracker data to the blockchain-

based distributed ledger.

It should be observed that in the data structures we

classiﬁed the payload on the basis of the data which

it refers, using the term local to indicate that gener-

ated by the entity and global to indicate that gener-

ated by the tracker, which also includes the local pay-

load. The data anonymity and data immutability of-

fered by a blockchain-based distributed ledger, joined

with the low-cost of the devices needed for the data

transmission and with the wireless coverage offered

by the ever increasing number of wireless-based de-

vices, given life to a powerful environment on which

is based the proposed IoE paradigm.

The data that we need to store on the blockchain-

based distributed ledger is that described in Section 3:

the ﬁrst ﬁeld i contains the GUID of the IoE entity;

the ﬁeld E

contains, when it is applicable, a list of

GUIDs related to the other entities captured together

with the entity e in a deﬁned temporal frame τ; the l

ﬁeld contains the geographic location (i.e., l ∈ L) of

the tracker that detected the entity e; the ﬁeld t reports

when the data capture event occurred, in the format

yyyy-mm-dd-hh-mm-ss; the last ﬁeld P contains a se-

ries of values in the format key,value which refer to

the sensors data of the entity (local payload) and to

the sensors data of the tracker (global payload).

It should be added that the information related to

the geographic location of an entity may be classiﬁed

according to its different resolution, which depends

on the operative range of the tracker.

Software Procedures: The software to use in order to

perform the entity-tracker and tracker-ledger commu-

nications has to fulﬁll the IoE paradigm needs, from

the entity-detection to the data-registration, by per-

forming the following operations:

i. entity-side: it broadcasts the entity GUID and pay-

load (i.e., local sensors data), by using the built-in

SENSORNETS 2019 - 8th International Conference on Sensor Networks

wireless device functionality;

ii. tracker-side: it performs a listening activity aimed

to detect and recognize entities within its wireless

coverage area (distinguishing them from the other

devices by using, for instance, a GUID preamble);

iii. tracker-side: it appends the tracker data (i.e., pri-

mary and payload data) with the data transmitted

by the entity (i.e., GUID and payload), prepar-

ing the data for the registration on the blockchain-

based distributed ledger;

iv. tracker-side: it submits the deﬁned data packet on

the blockchain-based distributed ledger, in order

to perform an immutable registration of the entity

activity;

v. tracker-side: it waits in order to receive from the

blockchain-based distributed ledger the registra-

tion acknowledge of the submitted packet, other-

wise it repeats the data submission.

A series of custom data-dashboards (i.e., a manage-

ment tool able to display, track, and analyze a series

of information) can be also designed in order to man-

age all the processes involved in the IoE paradigm.

The needed data, for instance those related to an entity

e, can be obtained by querying the Blockchain-based

distributed ledger, as shown in Algorithm 1.

5 FUTURE DIRECTIONS

As happened with other similar technologies, even in

the case of the proposed IoE one, the greatest obsta-

cle to overcome is the spread across users of such a

technology. Although it is possible to create a new

network of devices that operate according to the pro-

posed IoE paradigm, we can substantially reduce this

problem by integrating the IoE network into the exist-

ing wireless-based ones (e.g., IoT and mobile). This

process, which allows us to maximize the IoE poten-

tial, can be facilitate by adopting several strategies,

such as, the following ones:

i. designing simple and transparent procedure of

Algorithm 1: Ledger data gathering.

Require: e=Entity, R=Blockchain-based distributed ledger registrations

Ensure:

R=Registrations related to entity e

1: procedure GETENTITYREGISTRATIONS(e, R)

2: for each r in R do

3: i ← getEntityGUID(r)

4: if i(e) == ˆe then

R ← r(e)

6: end if

7: end for

8: return

9: end procedure

integration of the needed IoE functionalities in

the existing trackers, for instance, by integrating

these as a service in the new devices, by recurring

to a simple ﬁrmware/software upgrade process, or

by making available an application, in those cases

where the trackers or the entities are implemented

in devices that allow us this solution (e.g., smart-

phones, tablets, etc.);

ii. making effective campaigns of information aimed

to underline the advantages for each user that joins

the IoE network, empathizing the gained opportu-

nity to exchange information among a large com-

munity of users, an huge amount of valuable data

that they can exploit in many contexts;

iii. offering beneﬁts to the users that join their de-

vices to the IoE network as trackers, allowing

the system to perform the entity detection and the

distributed-ledger registration tasks. Such a ben-

eﬁts could include the free-use of some services

related to the IoE network.

6 CONCLUSION

This paper introduces a new data-exchange paradigm

that we baptized Internet of Entities (IoE). It has

been designed to join the capabilities offered by the

wireless-based devices environment with the certiﬁ-

cation capability offered by the blockchain-based dis-

tributed ledgers. Such an interaction is based on two

core components, entities and trackers, billion of de-

vices able to operate across the IoE environment, in-

terchangeably.

Although the proposed paradigm is based on ex-

isting and wide spread technologies, it offers a novel

way to trace in a certiﬁed and anonymous way the

activity of an entity, exploiting a combination of

wireless-based and blockchain-based technologies,

which produce valuable, exploitable, and (if needed)

investigative-valid data.

The concept of robust network in its unstructured

simplicity, expressed by Satoshi Nakamoto during

his Bitcoin formulation (Nakamoto, 2008), well de-

scribes also the Internet of Entities network, whose

potential capabilities are destined to grow, day af-

ter day, thanks to the continuous introduction of new

wireless-based devices, which provide an ever ex-

panding IoE coverage area.

Concluding, although the proposed IoE paradigm

can be easily implemented by exploiting existing and

wide spread technologies and infrastructures, it offers

a series of advantages for the community thanks to its

capability to operate in many real-world scenarios.

Internet of Entities (IoE): A Blockchain-based Distributed Paradigm for Data Exchange between Wireless-based Devices

ACKNOWLEDGEMENTS

This research is partially funded by: Regione

Sardegna under project Next generation Open Mo-

bile Apps Development (NOMAD), Pacchetti Inte-

grati di Agevolazione (PIA) - Industria Artigianato e

Servizi - Annualit

a 2013; Italian Ministry of Educa-

tion, University and Research - Program Smart Cities

and Communities and Social Innovation project

ILEARNTV (D.D. n.1937 del 05.06.2014, CUP

F74G14000200008 F19G14000910008).

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SENSORNETS 2019 - 8th International Conference on Sensor Networks